Fertility Awareness · Methods

Dynamic model for multivariate markers of fecundability

Cai B, Dunson DB, Stanford JB

Published September 16, 2009 Biometrics, 66(3), 905-913
DOI 10.1111/j.1541-0420.2009.01327.x PMID 19751248

Abstract

Dynamic latent class models provide a flexible framework for studying biologic processes that evolve over time. Motivated by studies of markers of the fertile days of the menstrual cycle, we propose a discrete-time dynamic latent class framework, allowing change points to depend on time, fixed predictors, and random effects. Observed data consist of multivariate categorical indicators, which change dynamically in a flexible manner according to latent class status. Given the flexibility of the framework, which incorporates semi-parametric components using mixtures of betas, identifiability constraints are needed to define the latent classes. Such constraints are most appropriately based on the known biology of the process. The Bayesian method is developed particularly for analyzing mucus symptom data from a study of women using natural family planning.

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Related research

Fertility Awareness › Methods › Billings Ovulation Method · Menstrual Cycle › Cycle Biomarkers › Cervical Mucus · Research Methods › Measurement and Statistics › Statistical Methods
Baigen Cai, Joseph B Stanford, David B Dunson
B Cai, Joe Stanford, Joey Stanford, J Stanford, Dave Dunson, D Dunson
PMID 19751248 19751248 DOI 10.1111/j.1541-0420.2009.01327.x 10.1111/j.1541-0420.2009.01327.x Cai et al. 2009, Cai 2009

Cite this article

Cai, B., Dunson, D. B., & Stanford, J. B. (2010). Dynamic model for multivariate markers of fecundability. Biometrics, 66(3), 905-913. https://doi.org/10.1111/j.1541-0420.2009.01327.x